Update app.py

app.py

@@ -5,6 +5,7 @@ import torch
 from utils import convert_segments_object_to_text, check_password, convert_segments_object_to_text_simple
 from gigiachat_requests import get_access_token, get_completion_from_gigachat, get_number_of_tokens, process_transcribation_with_gigachat
 from openai_requests import get_completion_from_openai, process_transcribation_with_assistant
+from qwen import respond
 
 if check_password():    
     st.title('Audio Transcription App')
@@ -19,12 +20,14 @@ if check_password():
 
     min_speakers = st.sidebar.number_input("Минимальное количество спикеров", min_value=1, value=2)
     max_speakers = st.sidebar.number_input("Максимальное количество спикеров", min_value=1, value=2)
-    llm = st.sidebar.selectbox("Производитель LLM", ["Сбер", "OpenAI"], index=0)
+    llm = st.sidebar.selectbox("Производитель LLM", ["Сбер", "OpenAI", "Qwen"], index=0)
 
     if llm == "Сбер":
         options = ["GigaChat-Plus", "GigaChat", "GigaChat-Pro"]
     elif llm == "OpenAI":
         options = ["gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4", "gpt-3.5-turbo"]
+    elif llm == "Qwen":
+        options = ["Qwen/Qwen2-7B-Instruct"]
     else:
         options = []
 
@@ -100,12 +103,18 @@ if check_password():
                 elif (llm == 'OpenAI'):
                     transcript = process_transcribation_with_assistant(processing_prompt, transcript)
                     print(transcript)
+
+                else:
+                    st.write("На данный момент обработка транскрибации не поддерживается этой моделью.")
     
         with st.spinner('Резюмируем...'):
             if (llm == 'Сбер'):
                 summary_answer = get_completion_from_gigachat(base_prompt + transcript, 1024, access_token, llm_model)
             elif (llm == 'OpenAI'):
-                summary_answer = get_completion_from_openai(base_prompt + transcript,llm_model, 1024)
+                summary_answer = get_completion_from_openai(base_prompt + transcript, llm_model, 1024)
+            elif (llm == 'Qwen'):
+                summary_answer = respond(base_prompt + transcript)
+                
         
             st.write("Результат резюмирования:")
             st.text(summary_answer)